Image de couverture de livre

Deep Neural Network-Driven Adaptive Filtering

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Wang, Qizhen, Wang, Gang, Liang, Ying-Chang
Format:	Preprint
Publié:	2025
Sujets:	Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Stability to Deformations of Manifold Filters and Manifold Neural Networks
par: Wang, Zhiyang, et autres
Publié: (2021)

Rethinking Spectral Graph Neural Networks with Spatially Adaptive Filtering
par: Guo, Jingwei, et autres
Publié: (2024)

Text-Driven Neural Collaborative Filtering Model for Paper Source Tracing
par: Xu, Aobo, et autres
Publié: (2024)

Missing Data Imputation by Reducing Mutual Information with Rectified Flows
par: Yu, Jiahao, et autres
Publié: (2025)

Causal Convolutional Neural Networks as Finite Impulse Response Filters
par: Bacsa, Kiran, et autres
Publié: (2025)

Adaptive Tabu Dropout for Regularization of Deep Neural Network
par: Hasan, Md. Tarek, et autres
Publié: (2024)

Data-Driven Graph Filters via Adaptive Spectral Shaping
par: Sandfelder, Dylan, et autres
Publié: (2026)

A Survey on Deep Neural Networks in Collaborative Filtering Recommendation Systems
par: Li, Pang, et autres
Publié: (2024)

High-Dimensional Differential Parameter Inference in Exponential Family using Time Score Matching
par: Williams, Daniel J., et autres
Publié: (2024)

Model Based and Physics Informed Deep Learning Neural Network Structures
par: Mohammad-Djafari, Ali, et autres
Publié: (2024)

Noise-Adaptive Layerwise Learning Rates: Accelerating Geometry-Aware Optimization for Deep Neural Network Training
par: Hao, Jie, et autres
Publié: (2025)

Towards Fair Graph Neural Networks via Graph Counterfactual without Sensitive Attributes
par: Wang, Xuemin, et autres
Publié: (2024)

General Formulation and PCL-Analysis for Restless Bandits with Limited Observability
par: Liu, Keqin, et autres
Publié: (2023)

Deep Recurrent Stochastic Configuration Networks for Modelling Nonlinear Dynamic Systems
par: Dang, Gang, et autres
Publié: (2024)

Calibrating Deep Neural Network using Euclidean Distance
par: Liang, Wenhao, et autres
Publié: (2024)

Towards Certified Unlearning for Deep Neural Networks
par: Zhang, Binchi, et autres
Publié: (2024)

Understanding Heterophily for Graph Neural Networks
par: Wang, Junfu, et autres
Publié: (2024)

Semantic Communication-Enhanced Split Federated Learning for Vehicular Networks: Architecture, Challenges, and Case Study
par: Yu, Lu, et autres
Publié: (2026)

Network Tomography with Path-Centric Graph Neural Network
par: Hu, Yuntong, et autres
Publié: (2025)

SF-GNN: Self Filter for Message Lossless Propagation in Deep Graph Neural Network
par: Zhu, Yushan, et autres
Publié: (2024)

Deep Neural Networks are Adaptive to Function Regularity and Data Distribution in Approximation and Estimation
par: Liu, Hao, et autres
Publié: (2024)

Gradient Residual Connections
par: Pan, Yangchen, et autres
Publié: (2026)

SGD with Partial Hessian for Deep Neural Networks Optimization
par: Sun, Ying, et autres
Publié: (2024)

Set-Valued Sensitivity Analysis of Deep Neural Networks
par: Wang, Xin, et autres
Publié: (2024)

Dual-Frequency Filtering Self-aware Graph Neural Networks for Homophilic and Heterophilic Graphs
par: Yang, Yachao, et autres
Publié: (2024)

Self-similarity Analysis in Deep Neural Networks
par: Ding, Jingyi, et autres
Publié: (2025)

Composite Reward Design in PPO-Driven Adaptive Filtering
par: Bereketoglu, Abdullah Burkan
Publié: (2025)

FGFP: A Fractional Gaussian Filter and Pruning for Deep Neural Networks Compression
par: Tu, Kuan-Ting, et autres
Publié: (2025)

Adaptive Gradient Regularization: A Faster and Generalizable Optimization Technique for Deep Neural Networks
par: Jiang, Huixiu, et autres
Publié: (2024)

Extended Deep Adaptive Input Normalization for Preprocessing Time Series Data for Neural Networks
par: September, Marcus A. K., et autres
Publié: (2023)

TSFLora: Token-Compressed Split Fine-Tuning for Wireless Edge Networks
par: Qiang, Xianke, et autres
Publié: (2026)

AB-PINNs: Adaptive-Basis Physics-Informed Neural Networks for Residual-Driven Domain Decomposition
par: Botvinick-Greenhouse, Jonah, et autres
Publié: (2025)

ATP: Adaptive Threshold Pruning for Efficient Data Encoding in Quantum Neural Networks
par: Afane, Mohamed, et autres
Publié: (2025)

Depth-induced NTK: Bridging Over-parameterized Neural Networks and Deep Neural Kernels
par: Tian, Yong-Ming, et autres
Publié: (2025)

Data-Driven Extended Corresponding State Approach for Residual Property Prediction of Hydrofluoroolefins
par: Wang, Gang, et autres
Publié: (2025)

Improving Generalization of Deep Neural Networks by Leveraging Margin Distribution
par: Lyu, Shen-Huan, et autres
Publié: (2018)

Geometric and Spectral Alignment for Deep Neural Network I
par: Liu, Ziran, et autres
Publié: (2026)

Geometric and Spectral Alignment for Deep Neural Network II
par: Liu, Ziran, et autres
Publié: (2026)

SDE-Driven Spatio-Temporal Hypergraph Neural Networks for Irregular Longitudinal fMRI Connectome Modeling in Alzheimer's Disease
par: Chen, Ruiying, et autres
Publié: (2026)

Eau De $Q$-Network: Adaptive Distillation of Neural Networks in Deep Reinforcement Learning
par: Vincent, Théo, et autres
Publié: (2025)